Importance Of Urinary Mitochondrial DNA in Diagnosis And Prognosis Of Kidney Diseases

Contact: Audrey Hu Whatsapp/hp: 0086 13880143964 Email: audrey.hu@wecistanche.com

Minjie Zhang, et al

Abstract

Mitochondrial injury plays an important role in the occurrence and development of kidney diseases. However, the existing assays to determine mitochondrial function restrict our ability to understand the relationship between mitochondrial dysfunction and kidney damage. These limitations may be overcome by recent findings on urinary mitochondrial DNA (UMT DNA). Elevated UmtDNA level may serve as a surrogate biomarker of mitochondrial dysfunction, kidney damage, and progression and prognosis of kidney diseases. Herein, we review the recent research progress on UmtDNA in kidney diseases diagnosis and highlight the research areas that should be expanded in the future as well as discuss the future perspectives.

Keywords: Urinary mitochondrial DNA Mitochondrial dysfunction Biomarker Kidney diseases

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1. Introduction

Kidney diseases have a long course and are difficult to cure, which impose a heavy burden on patients and society (Morton et al., 2018; Morton and Shah, 2021). According to a recent study; the annual cost of acute kidney injury (AKI)-related hospitalization in England was estimated to be £1.02 billion, slightly higher than 1% of the National Health Service budget. Furthermore, the lifetime cost of post-discharge care for AKI patients admitted during 2010–11 was estimated to be £179 million (Kerr et al., 2014). In 2017; approximately 700 million cases of chronic kidney disease (CKD) were reported, making it the 12th leading cause of death (Global, regional, and national burden of chronic kidney disease, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017, 2020); it is important to study the pathogenesis of renal injury and develop better therapeutic drugs for the treatment of kidney diseases.

In recent years, emerging evidence has shown that renal mitochondrial dysfunction plays an important role in the pathogenesis of kidney diseases (Che et al., 2014), especially AKI and CKD (Tang et al., 2021). Further, various quality control mechanisms, such as mitochondrial dynamics, mitophagy and biogenesis, and antioxidant defense mechanisms maintain mitochondrial homeostasis under physiological and pathological conditions (Tang et al., 2021). However, loss of these quality control mechanisms results in mitochondrial damage and dysfunction, leading to cell death, tissue damage, and potentially organ failure. The results of animal experiments showed that the deletion of Drp1, involved in mitochondria fission, attenuates AKI (Perry et al., 2018), whereas, the deletion of Pink1 and Park2, involved in mitophagy (Tang et al., 2018), and global Pgc1α, involved in the regulation of mitochondrial biogenesis (Tran et al., 2016), aggravates AKI. Furthermore, excessive reactive oxygen species production plays a key role in the development of CKD (Wei and Szeto, 2019).

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Traditionally, mitochondrial dysfunction is detected based on the measurement of the oxidative phosphorylation process in isolated mitochondrial, cellular, or tissue samples, in vivo (Wei and Szeto, 2019). For isolated mitochondria, the best method is the measurement of mitochondrial respiratory control, i.e., an increase in the respiratory rate in response to adenosine diphosphate, whereas, for intact cells, the best method is the equivalent measurement of cellular respiratory control, which assesses the adenosine triphosphate production rate, the proton leak rate, the coupling efficiency, the maximum respiration rate, the respiratory control ratio, and the reserve respiration volume (Brand and Nicholls, 2011).

However, due to the complexity of the traditional methods used for detecting mitochondrial dysfunction and the lack of practical methods for detecting renal mitochondrial injury and dysfunction, more specific, sensitive, and rapid biomarkers are needed for the early detection and monitoring of renal mitochondrial injury. Recent studies have demonstrated that renal dysfunction and mitochondrial damage can be detected using urinary mitochondrial DNA (mtDNA); hence, UmtDNA may be used for the diagnosis of renal injury and may help in revealing the relationship between renal injury and mitochondrial function and integrity. In this review, we summarize the potential value of mtDNA as a biomarker for AKI and CKD.

2. Features of mtDNA

Unlike the nuclear genome, mitochondria have their own unique genome, known as mitochondrial DNA (mtDNA), which is located in the organelle matrix and enclosed in a double membrane system consisting of external and internal mitochondrial membranes (Eirin et al., 2016). MtDNA is a 16.5 kb, circular, intron-free, double-stranded haploid DNA strand that encodes 37 genes (Castellani et al., 2020). In humans, the mtDNA encodes 13 proteins, all of which are the components of the electron transport chain (Fig. 1), and are essential for oxidative phosphorylation (Wallace, 2010).

The mtDNA is known to be more vulnerable to oxidative damages than nuclear DNA because of various reasons. First, mtDNA is not protected by histones and is located near the mitochondrial membrane, where reactive oxygen species are produced (Tanaka and Ozawa, 1994). Second, owing to the asymmetric replication of mtDNA, the heavy strand remains in a single-stranded state for a long time, making it more prone to spontaneous deamination (Tanaka and Ozawa, 1994). Third, compared to genomic DNA, lower reactive oxygen species concentration can cause damage to mtDNA, and further, the repairing process of mtDNA damage is slower than that of genomic DNA under long-term oxidative stress (Sharma and Sampath, 2019).

When mitochondria are damaged, their content, including mtDNA is released into the extracellular space and then into the systemic circulation (Zhang et al., 2010; Oka et al., 2012). The mtDNA fragments present in the systemic circulation are then filtered through the glomeruli and are actively secreted into the urine. Thus, cell-free mtDNA is found in blood, urine, and other tissues. Hence, the extracellular mtDNA level may serve as a surrogate marker of mitochondrial dysfunction and sublethal tissue damage (Wei and Szeto, 2019). Furthermore, the amount of mtDNA in body fluids can be easily quantified using quantitative PCR, which determines the copy number of mtDNA (Rooney et al., 2015). In addition, free mtDNA has been reported to be detected in plasma and explored as a biomarker for various diseases (Tin et al., 2016; Zhang et al., 2017; Nakahira et al., 2013; Cao et al., 2014; Lee et al., 2009; Wang et al., 2011; Mishra et al., 2016).

3. Source and content of mtDNA

As kidneys are the second most in mitochondrial abundance (Galvan et al., 2017), their damage results in the damage of mtDNA and its leakage from the renal parenchymal cells into the urine (Fig. 1) (Yu et al., 2019; Wei et al., 2018; Wei et al., 2018; Eirin et al., 2019; Eirin et al., 2017). Additionally, the circulating mtDNA filtered through the kidneys and released into the urine contributes to UmtDNA (Wei and Szeto, 2019; Cao et al., 2019; Huang et al., 2020). mtDNA is mainly measured based on the copy numbers of mitochondrial nicotinamide adenine dinucleotide dehydrogenase subunit 1 (mtND1) and cytochrome-c oxidase subunit III (mtCOX III) using quantitative PCR. COX III encodes the terminal enzyme of the mitochondrial respiratory chain (MRC)-IV, which catalyzes the transfer of electrons from reduced cytochrome C to oxygen, whereas, ND1 encodes a subunit of the MRC-I enzyme, which is responsible for the first step of the electron transport chain during electron transfer from nicotinamide adenine dinucleotide to ubiquinone. Moreover, these genes are located in relative positions on the circular mtDNA (Fig. 1) and may represent mtDNA functionally and anatomically (R¨ otig and Munnich, 2003). Therefore, it is relatively reliable to detect mtDNA levels based on mtND1 and mtCOX III copy numbers.

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4. Association between mtDNA and the progression of AKI

Accumulating evidence suggests the association between mtDNA and AKI. Recently, clinical studies have reported a significant elevation in UmtDNA levels in patients with AKI compared to those without AKI (Hu et al., 2018; Hu et al., 2017). Furthermore, the studies revealed that UmtDNA is negatively correlated with estimated glomerular filtration rate (eGFR), while positively correlated with renal injury markers, such as serum creatine and neutrophil gelatinase-associated lipocalin (Hu et al., 2018). Hence, these findings indicate that elevated UmtDNA levels may be used as an indicator of renal damage and decreased kidney function.

A study by Whitaker et al. found no increase in mtDNA in patients with AKI following cardiac surgery compared to those without AKI (Whitaker et al., 2015). However, when the patients were classified into three groups based on Acute Kidney Injury Network (AKIN) criteria (no AKI, AKIN 0 throughout follow-up; stable AKI, AKIN 1 + at collection, maximum AKIN = collection AKIN; and progressive AKI, AKIN 1 + at collection, maximum AKIN＞collection AKIN), UmtDNA was found to be significantly enriched in patients with progressive AKI compared to the patients with no or stable AKI (Whitaker et al., 2015). Moreover, the authors demonstrated a renal ischemia time-dependent increase in UmtDNA levels using a mouse model of renal ischemia-reperfusion injury. Consistently, Jansen et al. (Jansen et al., 2020) revealed that the mtDNA levels are correlated with the degree of cold ischemia time in renal transplant recipients. Thus, these findings indicate an association between UmtDNA and kidney injury.

Additionally, Whitaker et al. showed that both renal cortical mtDNA copy number and renal mitochondrial gene expression levels were reduced following ischemia-reperfusion, in vivo, and were inversely correlated with UmtDNA levels (Whitaker et al., 2015). These results were in agreement with the findings from a study by Hu et al., following sepsis, in vivo (Hu et al., 2018), indicating that UmtDNA is a reflection of renal mitochondrial disruption following AKI.

AKI is characterized by subfascial and fatal tubular injury (Tang et al., 2021). After the injury, the coordinated tissue repair response is activated to promote the recovery of sublethally injured cells, remove necrotic cells and debris, and reconstruct an intact, polarized renal epithelium (Whitaker et al., 2015). Furthermore, complete renal repair following a mild injury can lead to complete functional recovery, while the incomplete or maladaptive repair is often associated with severe or recurrent AKI, leading to nephritic unit loss, tubulointerstitial fibrosis, and eventual progression to CKD (Tang et al., 2021). The repair of renal tubular epithelium is a highly energy-dependent process; hence mitochondrial function is essential for the structural and functional recovery of the kidney (Tang et al., 2021). The receiver operator characteristic curve analysis by Whitaker et al. demonstrated that UmtDNA predicted AKI progression (Whitaker et al., 2015). Similarly, studies by Hu et al. (Hu et al., 2018; Hu et al., 2017) revealed UmtDNA-predicted development of AKI in sepsis or surgical intensive care unit patients. Further, these results have been confirmed in mouse (Whitaker et al., 2015) and rat (Hu et al., 2018)models of AKI. As mitochondrial disruption results in energy depletion and incomplete renal repair (Ho et al., 2017), the UmtDNA levels may serve as a valuable marker of AKI progression and as a prognostic indicator of renal injury repair.

5. Association between UmtDNA and the progression of CKD

In addition to AKI, UmtDNA may serve as an indicator of kidney damage in CKD, including diabetic nephropathy (DN) (Wei et al., 2018; Cao et al., 2019)and non-diabetic kidney disease (Wei et al., 2018; Wei et al., 2018).

5.1. UmtDNA in DN

UmtDNA has been shown to be correlated with the prognosis of CKD. Chang et al. found a significant correlation between low UmtDNA levels and favorable renal outcomes at six months in patients with advanced CKD (Chang et al., 2019). Furthermore, Wei et al. observed that UmtDNA level was significantly inversely correlated with eGFR, and positively correlated with interstitial fibrosis in biopsy-proven DN patients. However, mtDNA within the kidney had a significant inverse correlation with interstitial fibrosis (Wei et al., 2018). Hence, these findings suggest that the mitochondria of the kidney cells are damaged in the diabetic state, and the mtDNA is excreted through urine following injury.

Furthermore, a few other studies have shown that acquired mitochondrial dysfunction is an important factor in the progression of DN (Che et al., 2014; Hallan and Sharma, 2016; Higgins and Coughlan, 2014). Cao et al. (Cao et al., 2019) found elevated levels of UmtDNA in patients with type 2 diabetes mellitus (T2DM) and diabetic mice, during the early stages of DN. However, the level of intra-renal mtDNA was found to be decreased. Additionally, high glucose concentration inhibited the level of intracellular mtDNA and promoted its release, in vitro. Thus, during diabetes, excessive filtration of mtDNA through the kidneys is involved in chronic renal inflammation and may contribute to the progression of diabetic nephropathy (Cao et al., 2019). These observations are in agreement with the theory that mtDNA when released outside the cell, acts as an agent for damage-related molecular patterns, and causes inflammation (Zhang et al., 2010; Oka et al., 2012).

5.2. UmtDNA in non-diabetic CKD

Wei et al. (Wei et al., 2018) observed UmtDNA levels to be associated with proteinuria and rate of GFR decline in CKD patients with hypertensive nephrosclerosis and immunoglobulin A nephropathy and predicted the risk of doubling of serum creatinine or requirement of dialysis. Furthermore, multivariate Cox analysis showed that UmtDNA level is a predictor of renal survival (Wei et al., 2018). This model indicated that the risk of doubling serum creatinine or need for dialysis increased by 25% for every 100 copies/μL increase in UmtDNA. Yu et al. (Yu et al., 2019) observed that the changes in urinary mtND1 and mtCOX III were positively correlated with the changes in proteinuria following drug treatment, whereas, negatively correlated with the changes in eGFR in patients with immunoglobulin A nephropathy. Hence, the UmtDNA levels may serve as a prognostic indicator in nondiabetic CKD.

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6. Association between UmtDNA and other kidney diseases

Several studies have shown elevated UmtDNA levels in various other kidney diseases, including minor glomerular abnormalities (MGAs) (Yu et al., 2019), anti-neutrophil cytoplasmic antibody-associated vasculitis (AAV) (Wu et al., 2020), hypertension (Eirin et al., 2016; Eirin et al., 2019; Eirin et al., 2017), obesity (Lee et al., 2019; Seo et al., 2020), and kidney transplant surgery (Table 1) (Jansen et al., 2020; Kim et al., 2019).

6.1. UmtDNA in MGAs and AAV

Elevated UmtDNA levels have been observed in patients with MGAs compared to matched healthy controls (Yu et al., 2019). Yu et al. observed that the MGA patients exhibited differences in the time × group effects of eGFR, higher average annual rates of eGFR decrease, and higher UmtDNA copy numbers compared to matched healthy controls (Yu et al., 2019). These findings indicate that MGAs are associated with long-term deterioration of kidney function and mitochondrial damage.

The mean level of UmtDNA was significantly higher in AAV patients than that in the normal control group (Wu et al., 2020). Furthermore, multivariate correlation analysis indicated UmtDNA to be negatively correlated with eGFR. In addition, patients who needed dialysis at disease onset and got recovered had higher UmtDNA than those who remained under dialysis (Wu et al., 2020). Thus, these findings suggest that UmtDNA may be a useful biomarker for assessing kidney injury of AAV.

6.2. UmtDNA in hypertension

UmtDNA was found to be significantly elevated in patients with essential hypertension and renovascular hypertension compared to healthy volunteers, positively correlated with urinary neutrophil gelatinase-associated lipocalin and kidney injury molecule-1, and negatively correlated with eGFR (Eirin et al., 2016). Furthermore, a positive correlation was observed between UmtDNA copy number and renal hypoxia in renovascular hypertension patients (Eirin et al., 2016). However, there was a negative correlation between elevated UmtDNA levels and renal mitochondrial density, when mitochondrial damage in renal tubular epithelial cells was observed using electron microscopy in pigs with renovascular hypertension (Eirin et al., 2019). Hence, these results suggest that UmtDNA may act as a marker of renal damage and dysfunction under hypertension.

6.3. UmtDNA in obesity

Obesity is an independent risk factor for chronic kidney disease (Kalantar-Zadeh and Kopple, 2006), and has been found to be associated with increased UmtDNA. A clinical trial on age and sex-matched obese patients and healthy volunteers showed that the copy number of urinary mtND1 was significantly higher in the obese group than in healthy volunteers. However, no changes in urinary mtCOX III were observed between these groups (Lee et al., 2019), suggesting that obesity may have a greater effect on MRC-I. In another study, copy numbers of urinary mtND1 and mtCOX III were found to be higher in obese patients with or without T2DM than in healthy volunteers (Seo et al., 2020). In addition, the copy number of urinary mtCOX III was higher in obese patients with T2DM than in patients without T2DM, suggesting that the effects of diabetes on renal MRC may be mainly manifested in MRC-IV, in obese patients. Thus, the findings from these studies show that UmtDNA may be an important potential marker for renal mitochondrial damage in obesity.

6.4. UmtDNA in kidney transplantation

Renal ischemia time is a major determinant of renal ischemia-reperfusion injury and subsequent renal function and is prone to induce delayed graft function (DGF) (Mikhalski et al., 2008). UmtDNA was found to be elevated after kidney transplantation, and cold ischemia time and renal function were found to be associated with UmtDNA. Furthermore, UmtDNA levels were significantly higher in the DGF group than in the non-DGF group (Jansen et al., 2020). In addition, UmtDNA level was negatively correlated with eGFR, while it was positively correlated with urine neutrophil gelatinase-associated lipocalin levels. In particular, patients with DGF and cases with acute rejection showed higher levels of UmtDNA (Kim et al., 2019), suggesting that UmtDNA level is a sensitive indicator of renal graft injury, and may be used as a noninvasive marker for the prognosis of DGF after renal transplantation.

7. Conclusions and future directions

Current evidence suggests that UmtDNA may serve as a novel biomarker for both kidney damage and renal mitochondrial injury. In contrast to the existing biomarkers of renal impairment, detection of UmtDNA is noninvasive. Further, it is easy to collect UmtDNA for continuous evaluation of changes associated with renal function and renal repair processes in AKI patients. Most studies have shown a positive correlation between UmtDNA and indicators of kidney functions. However, a few studies did not show any correlation, which may be attributed to the existing renal function indicators (e.g., blood urea nitrogen and serum creatinine) that could not indicate early renal injury (Ferguson et al., 2008), and the small-scale clinical studies. Therefore, there is an urgent need to perform studies with more samples, larger multi-center studies, and animal model-based studies to further determine the potential value of UmtDNA as well as to determine the normal range and grading of UmtDNA level.

Since UmtDNA may be derived from the damaged renal parenchymal cells, as well as from circulating blood filtered through the kidneys, it is of great importance to specifically identify UmtDNA contributed primarily by the kidneys to better understand the mitochondrial damage in the kidneys. Hence, measurements of circulating mtDNA levels could overcome this limitation (Yu et al., 2019).

Furthermore, UmtDNA may serve as a predictive biomarker of AKI development and progression, and as a novel prognostic biomarker for renal outcome in CKD patients. However, the small sample size may introduce the type I statistical error (Wei et al., 2018). Hence, studies with a large number of patients with varying degrees of kidney diseases and multiple etiologies are needed to verify the predictive power of UmtDNA.

In summary, UmtDNA may be considered a valuable biomarker for renal mitochondrial damage, progression of AKI, and the prognosis of CKD, and may be used for the development of mitochondrial-targeted therapies for nephrotic patients.

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Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

This research was funded by the Guangdong Basic and Applied Basic Research Foundation (No. 2020A1515111080) and the National Natural Science Foundation of China (No. 82000647).

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